Brain tumors are a primary factor causing cancer-related deaths globally, and their classification remains a significant research challenge due to the variability in tumor intensity, size, and shape, as well as the similar appearances of different tumor types. Accurate differentiation is further complicated by these factors, making diagnosis difficult even with advanced imaging techniques such as magnetic resonance imaging (MRI). Recent techniques in artificial intelligence (AI), in particular deep learning (DL), have improved the speed and accuracy of medical image analysis, but they still face challenges like overfitting and the need for large annotated datasets. This study addresses these challenges by presenting two approaches for brain tumor classification using MRI images. The first approach involves fine-tuning transfer learning cutting-edge models, including SEResNet, ConvNeXtBase, and ResNet101V2, with global average pooling 2D and dropout layers to minimize overfitting and reduce the need for extensive preprocessing. The second approach leverages the Vision Transformer (ViT), optimized with the AdamW optimizer and extensive data augmentation. Experiments on the BT-Large-4C dataset demonstrate that SEResNet achieves the highest accuracy of 97.96%, surpassing ViT’s 95.4%. These results suggest that fine-tuning and transfer learning models are more effective at addressing the challenges of overfitting and dataset limitations, ultimately outperforming the Vision Transformer and existing state-of-the-art techniques in brain tumor classification.

The potential of nanotechnology to improve human health, optimize natural resource utilization, and reduce environmental pollution is remarkable. With the ever-growing advancement in dentistry, one of the breakthroughs is using nanotechnology. Nanotechnology in periodontics has touched every aspect of treatment modality, from non-surgical therapy to implant procedures, including regenerative procedures. Understanding their mechanism plays a pivotal role in more efficient usage of nanotechnology, better treatment procedures, and eventually better outcomes. In this paper, we review the application of nanotechnology in periodontal therapy. We performed the search for papers in Scopus using the key words and phrases as follows: “nanodentistry”; “dentistry and nanotechnology”; “dentistry and nanoparticles”; “dentistry and nanomedicine”; “dentistry and nanorobots”. There were found 530 papers in total. Some papers belonged to two and more categories. It is revealed that the number of papers versus year does not follow any specific pattern, but the cumulative amount of papers versus year is fitted with the exponential regression. There were also selected papers using certain inclusion/exclusion criteria. Only the selected papers were analyzed. Nanomedicine is subjected to intensive studies nowadays. There are some promising results that will likely be implemented into praxis soon in the fields of medical diagnostics and clinical therapeutics. The appearance of nanotechnology can have a considerable impact on the treatment of periodontal diseases.

We have studied the effect of the series resistance on the heating of the cathode, which is based on carbon nanotubes and serves to realize the field emission of electrons into the vacuum. The experiment was performed with the single multi-walled carbon nanotube (MCNT) that was separated from the array grown by CVD method with thin-film Ni-Ti catalyst (nickel 4 nm/Ti 10 nm). The heating of the cathode leads to the appearance of a current of the thermionic emission. The experimental voltage current characteristic exhibited the negative resistance region caused by thermal field emission. This current increases strongly with increasing voltage and contributes to the degradation of the cold emitter. The calculation of the temperature of the end of the cathode is made taking into account the effect of the phenomenon that warms up and cools the cathode. We have developed a method for processing of the emission volt-ampere characteristics of a cathode, which relies on a numerical calculation of the field emission current and the comparison of these calculations with experiments. The model of the volt-ampere characteristic takes into account the CNT’s geometry, properties, its contact with the catalyst, heating and simultaneous implementation of the thermionic and field emission. The calculation made it possible to determine a number of important parameters, including the voltage and current of the beginning of thermionic emission, the temperature distribution along the cathode and the resistance of the nanotube. The phenomenon of thermionic emission from CNTs was investigated experimentally and theoretically. The conditions of this type emission occurrence were defined. The results of the study could form the basis of theory of CNT emitter’s degradation.

The augmentation of firm performance via customer concentration is particularly indispensable for organizational evolution. Both trade credit financing and financing constraints play pivotal roles in the nexus between customer concentration and performance. This research constructs a moderated mediation model to rigorously investigate the impact of customer concentration on firm performance, positing trade credit financing as the mediating variable and financing constraints as the moderating variable. The relevant hypotheses are evaluated empirically using panel data compiled from listed manufacturing firms in China over the period 2013–2020, yielding 8 firm-year observations. The empirical outcomes denote that customer concentration exerts a positive influence on firm performance, albeit having a negative impact on trade credit financing. Trade credit financing serves as a partial mediator in the relationship between customer concentration and manufacturing firm performance. Financing constraints are found to positively moderate the mediating role of trade credit financing in the relationship between customer concentration and firm performance. This research broadens the understanding of the implications of customer relationships on trade credit financing and performance, thereby enriching the knowledge base for managing a firm’s financing channels more effectively.